Quickly search, compare, and analyze genomic and metagenomic data sets.
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Updated
Jun 19, 2025 - Python
Quickly search, compare, and analyze genomic and metagenomic data sets.
Fast taxonomic classification of metagenomic sequencing reads using a protein reference database
ultrafast taxonomic profiling and genome querying for metagenomic samples by abundance-corrected minhash.
Amplicon sequencing analysis workflow using DADA2 and QIIME2
Accurate metagenomic profiling && Fast large-scale sequence/genome searching
Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data
Metabuli: specific and sensitive metagenomic classification via joint analysis of DNA and amino acid.
Massively parallel phylogenetic placement of genetic sequences
Fast and accurate tool for calculating Average Nucleotide Identity (ANI) and clustering virus genomes and metagenomes
FlexTaxD (Flexible Taxonomy Databases) - Create, add, merge different taxonomy sources (QIIME, GTDB, NCBI and more) and create metagenomic databases (kraken2, ganon and more )
Create BIOM-format tables (http://biom-format.org) from Kraken output (http://ccb.jhu.edu/software/kraken/, https://github.com/DerrickWood/kraken).
Fast and space-efficient taxonomic classification of long reads
Tag and recommend Python exercises based on algorithmic features
PyTorch implementation of Metric-Guided Prototype Learning for hierarchical classification.
This repository contains all the source files required to run DeLUCS, a deep learning clustering algorithm for DNA sequences.
Lemur is a tool for rapid and accurate taxonomic profiling on long-read metagenomic datasets
A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.
CyanoSeq: A curated cyanobacterial 16S rRNA database for next-generation sequencing
A pipeline for taxonomic classification and functional annotation of metagenomic reads. Based on MEDUSA
📓 Companion code for Grenié et al. 2022 MEE "Harmonizing taxon names in biodiversity data: a review of tools, databases, and best practices" preprint: 10.32942/osf.io/e3qnz
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